在python中从熊猫数据框检索信息

Question

I have a pandas dataframe:

   Time(s)  RARb relative signal  Rescaled_CRABPII  atRA  RARa_tet  RARg_tet
0        0                     0          0.000000   100         0         0
1     7200                    20          0.000000   100         0         0
2    14400                    50         11.764706   100         0         0
3    21600                    90         58.823529   100         0         0
4    43200                   100        100.000000   100         0         0
5    50400                   100        105.882353   100         0         0
6    64800                   100        117.647059   100         0         0

How can I retrieve the value of RARb relative signal at df['Time(s)']==43200 ?

Answer 1

假设df为数据框，您可以：

a = df[df['Time(s)']==43200]['RARb relative signal']

Answer 2

First, if you keep the df as is, you should use .iat[] or .at[] instead for scalar getting and setting (see examples on .iat[] and .at[] [here] 1 ). So the .iat version (which is the faster of the two) would be:

val = df.iat[df['Time(s)']==43200, 1]

The column number is 1 because 'RARb relative signal' is the second column. If you're not sure what the column position will be you can either get that too with get_loc() or just use .at[] with label-based indexing:

val = df.at[df['Time(s)']==43200, 'RARb relative signal']

If you actually have a multiindex pass a tuple with all the multiindex levels instead of the single label.

Really though, why don't you make the time in seconds be the index? You could still use integer-based indexing to access items, and this approach seems to make much more sense for your data. First, reset the index:

df.index = df['Time(s)']

You may wish to then delete the 'Time(s)' column, that's up to you. Anyway with the new index you can just do:

val = df.at[43200, 'RARb relative signal'] 

If you're doing these sorts of value retrievals a lot, re-indexing and using .iat[] or .at[] can make a big performance difference.